Results for “air pollution” 112 found
We combine satellite-based pollution data and test scores from over 10,000 U.S. school districts to estimate the relationship between air pollution and test scores. To deal with potential endogeneity we instrument for air quality using (i) year-to-year coal production variation and (ii) a shift-share instrument that interacts fuel shares used for nearby power production with national growth rates. We find that each one-unit increase in particulate pollution reduces test scores by 0.02 standard deviations. Our findings indicate that declines in particulate pollution exposure raised test scores and reduced the black-white test score gap by 0.06 and 0.01 standard deviations, respectively.
I have not had the chance to read this through, but here goes:
Documenting environmental pollution damage affects the magnitude of aggregate output, net of pollution damage, and the contribution to national product across economic sectors. For example, air pollution damage from the production side of the economy amounted to over 5 percent of gross domestic product (GDP) in 2002…
I have presented estimates of these effects in the US economy between 1957 and 2016. This period featured the passage of the Clean Air Act (CAA) in 1970 and its subsequent implementation through the 1970s, as well as several business cycles. This research suggests that pollution damage began to decrease just after the CAA was enacted, and the orientation between GDP growth and that of the adjusted measure, or environmentally adjusted value added (EVA), switched.
If we use the standard measure of GDP, growth indeed slowed down after 1970. If instead we augment GDP for environmental damages, the period after 1970 was actually faster! The adjustment both slows down growth from 1957-1970, and speeds up growth after 1970.
Worth a ponder.
Great piece by David Wallace-Wells on air pollution.
Here is just a partial list of the things, short of death rates, we know are affected by air pollution. GDP, with a 10 per cent increase in pollution reducing output by almost a full percentage point, according to an OECD report last year. Cognitive performance, with a study showing that cutting Chinese pollution to the standards required in the US would improve the average student’s ranking in verbal tests by 26 per cent and in maths by 13 per cent. In Los Angeles, after $700 air purifiers were installed in schools, student performance improved almost as much as it would if class sizes were reduced by a third. Heart disease is more common in polluted air, as are many types of cancer, and acute and chronic respiratory diseases like asthma, and strokes. The incidence of Alzheimer’s can triple: in Choked, Beth Gardiner cites a study which found early markers of Alzheimer’s in 40 per cent of autopsies conducted on those in high-pollution areas and in none of those outside them. Rates of other sorts of dementia increase too, as does Parkinson’s. Air pollution has also been linked to mental illness of all kinds – with a recent paper in the British Journal of Psychiatry showing that even small increases in local pollution raise the need for treatment by a third and for hospitalisation by a fifth – and to worse memory, attention and vocabulary, as well as ADHD and autism spectrum disorders. Pollution has been shown to damage the development of neurons in the brain, and proximity to a coal plant can deform a baby’s DNA in the womb. It even accelerates the degeneration of the eyesight.
A high pollution level in the year a baby is born has been shown to result in reduced earnings and labour force participation at the age of thirty. The relationship of pollution to premature births and low birth weight is so strong that the introduction of the automatic toll system E-ZPass in American cities reduced both problems in areas close to toll plazas (by 10.8 per cent and 11.8 per cent respectively), by cutting down on the exhaust expelled when cars have to queue. Extremely premature births, another study found, were 80 per cent more likely when mothers lived in areas of heavy traffic. Women breathing exhaust fumes during pregnancy gave birth to children with higher rates of paediatric leukaemia, kidney cancer, eye tumours and malignancies in the ovaries and testes. Infant death rates increased in line with pollution levels, as did heart malformations. And those breathing dirtier air in childhood exhibited significantly higher rates of self-harm in adulthood, with an increase of just five micrograms of small particulates a day associated, in 1.4 million people in Denmark, with a 42 per cent rise in violence towards oneself. Depression in teenagers quadruples; suicide becomes more common too.
Stock market returns are lower on days with higher air pollution, a study found this year. Surgical outcomes are worse. Crime goes up with increased particulate concentrations, especially violent crime: a 10 per cent reduction in pollution, researchers at Colorado State University found, could reduce the cost of crime in the US by $1.4 billion a year. When there’s more smog in the air, chess players make more mistakes, and bigger ones. Politicians speak more simplistically, and baseball umpires make more bad calls.
As MR readers will know Tyler and I have been saying air pollution is an underrated problem for some time. Here’s my video on the topic:
That is the theme of my latest Bloomberg column, here is one excerpt:
More than 10 million people die each year from air pollution, according to a new study — far more than the estimated 2.6 million people who have died from Covid-19 since it was detected more than a year ago. And while Covid is headline news, ordinary air pollution remains a side issue for policy wonks and technocrats.
[To be clear, I am not seeking to minimize Covid as a major issue.] And:
Why aren’t these deaths a bigger issue in U.S. political and policy discourse? One reason may be that 62% of those deaths are in China and India. The number of premature deaths due to particulate matter in North America was 483,000, just slightly lower than the number of measured deaths from Covid to date. An estimated 876 of those deaths were of children under the age of 4.
Another reason for the weak political salience of the issue may be its invisibility. Air pollution causes many deaths. But it is rare to see or read about a person dying directly from air pollution. Lung cancer and cardiac disease are frequently cited as causes of death, even though they may stem from air pollution.
Another problem is that the question of how to better fight air pollution does not fit neatly into current ideological battles. You might think Democrats would emphasize this issue, but much of the economic burden of tougher action would fall on the Northeast, a largely Democratic-leaning area.
And exactly how many people die each year from global warming? Why not have a greater focus on ordinary air pollution?
The number and quality of studies showing that air pollution has very substantial effects on health continues to increase. Patrick Collison reviews some of the most recent studies on air pollution and cognition. I’m going to post the whole thing so everything that follows is Patrick’s.
Air pollution is a very big deal. Its adverse effects on numerous health outcomes and general mortality are widely documented. However, our understanding of its cognitive costs is more recent and those costs are almost certainly still significantly under-emphasized. For example, cognitive effects are not mentioned in most EPA materials.
World Bank data indicate that 3.7 billion people, about half the world’s population, are exposed to more than 50 µg/m³ of PM2.5 on an annual basis, 5x the unit of measure for most of the findings below.
- Substantial declines in short-term cognitive performance after short-term exposure to moderate (median 27.0 µg/m³) PM2.5 pollution: “The results from the MMSE test showed a statistically robust decline in cognitive function after exposure to both the candle burning and outdoor commuting compared to ambient indoor conditions. The similarity in the results between the two experiments suggests that PM exposure is the cause of the short-term cognitive decline observed in both.” […] “The mean average [test scores] for pre and post exposure to the candle burning were 48 ± 16 and 40 ± 17, respectively.” – Shehab & Pope 2019.
- Chess players make more mistakes on polluted days: “We find that an increase of 10 µg/m³ raises the probability of making an error by 1.5 percentage points, and increases the magnitude of the errors by 9.4%. The impact of pollution is exacerbated by time pressure. When players approach the time control of games, an increase of 10 µg/m³, corresponding to about one standard deviation, increases the probability of making a meaningful error by 3.2 percentage points, and errors being 17.3% larger.” – Künn et al 2019.
- A 3.26x (albeit with very wide CI) increase in Alzheimer’s incidence for each 10 µg/m³ increase in long-term PM2.5 exposure? “Short- and long-term PM2.5 exposure was associated with increased risks of stroke (short-term odds ratio 1.01 [per µg/m³ increase in PM2.5 concentrations], 95% CI 1.01-1.02; long-term 1.14, 95% CI 1.08-1.21) and mortality (short-term 1.02, 95% CI 1.01-1.04; long-term 1.15, 95% CI 1.07-1.24) of stroke. Long-term PM2.5 exposure was associated with increased risks of dementia (1.16, 95% CI 1.07-1.26), Alzheimer’s disease (3.26, 95% 0.84-12.74), ASD (1.68, 95% CI 1.20-2.34), and Parkinson’s disease (1.34, 95% CI 1.04-1.73).” – Fu et al 2019. Similar effects are seen in Bishop et al 2018: “We find that a 1 µg/m³ increase in decadal PM2.5 increases the probability of a dementia diagnosis by 1.68 percentage points.”
- A study of 20,000 elderly women concluded that “the effect of a 10 µg/m³ increment in long-term [PM2.5 and PM10] exposure is cognitively equivalent to aging by approximately 2 years”. – Weuve et al 2013.
- “Utilizing variations in transitory and cumulative air pollution exposures for the same individuals over time in China, we provide evidence that polluted air may impede cognitive ability as people become older, especially for less educated men. Cutting annual mean concentration of particulate matter smaller than 10 µm (PM10) in China to the Environmental Protection Agency’s standard (50 µg/m³) would move people from the median to the 63rd percentile (verbal test scores) and the 58th percentile (math test scores), respectively.” – Zhang et al 2018.
- “Exposure to CO2 and VOCs at levels found in conventional office buildings was associated with lower cognitive scores than those associated with levels of these compounds found in a Green building.” – Allen et al 2016. The effect seems to kick in at around 1,000 ppm of CO2.
Alex again. Here’s one more. Heissel et al. (2019):
“We compare within-student achievement for students transitioning between schools near highways, where one school has had greater levels of pollution because it is downwind of a highway. Students who move from an elementary/middle school that feeds into a “downwind” middle/high school in the same zip code experience decreases in test scores, more behavioral incidents, and more absences, relative to when they transition to an upwind school”
Relatively poor countries with extensive air pollution–such as India–are not simply choosing to trade higher GDP for worse health; air pollution is so bad that countries with even moderate air pollution are getting lower GDP and worse heath.
Addendum: Patrick has added a few more.
In recent years I have substantially increased my estimate of the deadly nature of air pollution. It’s not that I had a contrary opinion earlier but the number and range of studies showing surprisingly large effects has raised this issue in relative importance in my mind. I would not have guessed, for example, that the introduction of EZ Pass could reduce pollution near toll booths enough to reduce the number of premature and low birth weight babies. I also find the following result hard to believe yet also hard to dismiss given the the accumulating body of evidence. Diane Alexander and Hannes Schwandt find that Volkswagen’s cheating diesel cars increased the number of low birth weight babies and asthma rates. Here are some details:
In 2008, a new generation of supposedly clean diesel passenger cars was introduced to the U.S. market.These new diesel cars were marketed to environmentally conscious consumers, with advertising emphasizing the power and mileage typical for diesel engines in combination with unprecedented low emissions levels. Clean diesel cars won the Green Car of the Year Award in 2009 and 2010 and quickly gained market share. By 2015, over 600,000 cars with clean diesel technology were sold in the United States. In the fall of 2015, however, it was discovered that these cars covertly activated equipment during emissions tests that reduced emissions below official thresholds, and then reversed course after testing. In street use, a single “clean diesel” car could pollute as much nitrogen oxide as 150 equivalent gasoline cars.Hereafter, we refer to cars with “clean diesel” technology as cheating diesel cars.
We exploit the dispersion of these cheating diesel cars across the United States as a natural experiment to measure the effect of car pollution on infant and child health. This natural experiment provides several unique features. First, it is typically difficult to infer causal effects from observed correlations of health and car pollution, as wealthier individuals tend to sort into less-polluted areas and drive newer, less-polluting cars. The fast roll-out of cheating diesel cars provides us with plausibly exogenous variation in car pollution exposure across the entire socio-economic spectrum of the United States. Second, it is well established that people avoid known pollution, which can mute estimated impacts of air pollution on health (Neidell, 2009). Moderate pollution increases stemming from cheating diesel cars, a source unknown to the population, are less likely to induce avoidance behaviors, allowing us to cleanly estimate the full impact of pollution. Third, air pollution comes from a multitude of sources, making it difficult to identify contributions from cars, and it is measured coarsely with pollution monitors stationed only in a minority of U.S. counties. This implies low statistical power and potential attenuation bias for correlational studies of pollution (Lleras-Muney, 2010). We use the universe of car registrations to track how cheating diesel cars spread across the country and link these data to detailed information on each birth conceived between 2007 and 2015. This setting provides rich and spatially detailed variation in car pollution.
We find that counties with increasing shares of cheating diesel cars experienced large increases both in air pollution and in the share of infants born with poor birth outcomes. We show that for each additional cheating diesel car per 1,000 cars—approximately equivalent to a 10 percent cheating-induced increase in car exhaust—there is a 2.0 percent increase in air quality indices for fine particulate matter (PM2:5) and a 1.9 percent increase in the rate of low birth weight. We find similar effects on larger particulates (PM10; 2.2 percent) and ozone (1.3 percent), as well as reductions in average birth weight (-6.2 grams) and gestation length (-0.016 weeks). Effects are observed across the entire socio-economic spectrum, and are particularly pronounced among advantaged groups, such as non-Hispanic white mothers with a college degree. Effects on pollution and health outcomes are approximately linear and not affected by baseline pollution levels. Overall, we estimate that the 607,781 cheating diesel cars sold from 2008 to 2015 led to an additional 38,611 infants born with low birth weight. Finally, we also find an 8.0 percent increase in asthma emergency department (ED) visits among young children for each additional cheating diesel car per 1,000 cars in a subsample of five states.
Another surprising result is that on a global scale air pollution reduces life expectancy more than smoking. In part, because a single individual can’t quit air pollution.
Globally, the AQLI reveals that particulate pollution reduces average life expectancy by 1.8 years, making it the greatest global threat to human health. By comparison, first-hand cigarette smoke leads to a reduction in global average life expectancy of about 1.6 years. Other risks to human health have even smaller effects: alcohol and drugs reduce life expectancy by 11 months; unsafe water and sanitation take off 7 months; and HIV/AIDS, 4 months. Conflict and terrorism take off 22 days. So, the impact of particulate pollution on life expectancy is comparable to that of smoking, twice that of alcohol and drug use, three times that of unsafe water, five times that of HIV/AIDS, and more than 25 times that of conflict and terrorism.
There are now pollution red alerts in at least 24 cities in north China, so are things really hopeless in the Middle Kingdom? I say no. That is the topic of my latest Bloomberg column, here are some excerpts:
One famous paper, by economists Gene M. Grossman and Alan Krueger, found that (in current dollars) the turning point for environmental improvement comes in “almost every case” when countries reach the range of $17,000 to $18,000 in per capita annual income. Current Chinese per capita income can be plausibly estimated at over $14,000 per year. That means China may not be far from starting to clean up its air, and indeed air quality is already one of the major political issues in China.
The Chinese government already responds to pollution problems with factory closings and automobile restrictions more quickly than it used to, and in general there is better data and more transparency from policymakers. The U.S. Embassy in Beijing reports pollution improvements for particulate matter over the last year. Over the last two years, there have been suggestions, admittedly debatable ones, that China’s evolution into a service-sector economy means that the turning point already has been reached.
What about the U.S. and its history of fighting air pollution?
By my estimates (see the column), the United States started cleaning up at a per capita income of at least 28k (in current dollars), in the mid-1960s, arguably later than that date. In other words, if the Chinese waited to start cleaning up their air until they were about twice as rich as is currently the case, they still would be matching the pace of America.
Kai Xue writes:
But I say in plain honesty that terrible air pollution while taken as mandarin indifference to public demands is to the contrary a manifestation of commitment to a mass middle class by the Chinese political system.
Policy deliberately trades off public health for blue collar jobs. Around Beijing are industries including steel mills and cement plants that are major polluters. About 1 in 10 tonnes of the world’s steel output is smelted in Hebei, the province surrounding Beijing. With so much local heavy industry, cleaning the air would start with plant closures that cause concentrated unemployment.
Whether this bargain of clean air for economic growth is a good deal is a fair question but whether it is virtuous public policy depends on the extent decision-makers are subject to or instead insulated from the consequences of self-produced actions.
Beijing is the seat of power in a centralized state. About one third of the thousands who hold junior ministerial rank or higher and many of the very rich reside here.
Regardless of stature, for every Beijing inhabitant air pollution is the most serious public concern.
That is from an Atlantic article by James Fallows.
Perhaps the most pressing environmental problem in the world is indoor air pollution, which kills 2.8 million people each year, just behind HIV/AIDS. The pollution is caused by poor people cooking and heating their homes with dung and cardboard. The solution is not environmental (to certify dung) but rather economic, helping these people build enough wealth to afford kerosene.
That is by Bjorn Lomborg, in Foreign Policy, July/August issue.
Two caveats. First, the best figure I can find appears to be 1.6 million lives; here is a WHO statement on the phenomenon. Second, the people die because the smoke renders them more susceptible to pneumonia and other respiratory diseases. But their poverty makes them more susceptible for a number of reasons. I doubt if the marginal product of the smoke can be isolated clearly; see this study. Nonetheless this is a very very serious problem that does not receive much attention.
My recent post, Air Pollution Reduces Health and Wealth drew some pushback in the comments, some justified, some not, on whether the results of these studies are not subject to p-hacking, forking gardens and the replication crisis. Sure, of course, some of them are. Andrew Gelman, for example, has some justified doubt about the air filters and classroom study. Nevertheless, I don’t think that skepticism about the general thrust of the results is justified. Why not?
First, go back to my post Why Most Published Research Findings are False and note the list of credibility checks. For example, my rule is trust literatures not papers and the new pollution literature is showing consistent and significant negative effects of pollution on health and wealth. Some might respond that the entire literature is biased for reasons of political correctness or some such and sure, maybe. But then what evidence would be convincing? Is skepticism then justified or merely mood affiliation? And when it comes to action should we regard someone’s prior convictions (how were those formed?) as more accurate then a large, well-published scientific literature?
It’s not just that the literature is large, however, it’s that the literature is consistent in a way that many studies in say social psychology were not. In social psychology, for example, there were many tests of entirely different hypotheses–power posing, priming, stereotype threat–and most of these failed to replicate. But in the pollution literature we have many tests of the same hypotheses. We have, for example, studies showing that pollution reduces the quality of chess moves in high-stakes matches, that it reduces worker productivity in Chinese call-centers, and that it reduces test scores in American and in British schools. Note that these studies are from different researchers studying different times and places using different methods but they are all testing the same hypothesis, namely that pollution reduces cognitive ability. Thus, each of these studies is a kind of replication–like showing price controls led to shortages in many different times and places.
Another feature in favor of the air pollution literature is that the hypothesis that pollution can have negative effects on health and cognition wasn’t invented yesterday along with the test (we came up with a new theory and tested it and guess what, it works!). The Romans, for example, noted the negative effect of air pollution on health. There’s a reason why people with lung disease move to the countryside and always have.
I also noted in Why Most Published Research Findings are False that multiple sources and types of evidence are desirable. The pollution literature satisfies this desideratum. Aside from multiple empirical studies, the pollution hypothesis is also consistent with plausible mechanisms and it is consistent with the empirical and experimental literature on pollution and plants and pollution and animals. See also OpenPhilanthropy’s careful summary.
Moreover, there is a clear dose-response effect–so much so that when it comes to “extreme” pollution few people doubt the hypothesis. Does anyone doubt, for example, that an infant born in Delhi, India–one of the most polluted cities in the world–is more likely to die young than if the same infant grew up (all else equal) in Wellington, New Zealand–one of the least polluted cities in the world? People accept that “extreme” pollution creates debilitating effects but they take extreme to mean ‘more than what I am used to’. That’s not scientific. In the future, people will think that the levels of pollution we experience today are extreme, just as we wonder how people could put up with London Fog.
What is new about the new pollution literature is more credible methods and bigger data and what the literature shows is that the effects of pollution are larger than we thought at lower levels than we thought. But we should expect to find smaller effects with better methods and bigger data. (Note that this isn’t guaranteed, there could be positive effects of pollution at lower levels, but it isn’t surprising that what we are seeing so far is negative effects at levels previously considered acceptable.)
Thus, while I have no doubt that some of the papers in the new pollution literature are in error, I also think that the large number of high quality papers from different times and places which are broadly consistent with one another and also consistent with what we know about human physiology and particulate matter and also consistent with the literature on the effects of pollution on animals and plants and also consistent with a dose-response relationship suggest that we take this literature and its conclusion that air pollution has significant negative effects on health and wealth very seriously.
The long-held belief that pollution is the cost a country has to pay for development is no longer true as bad air quality has a measurable detrimental impact on human productivity that could in turn reduce GDP, Canadian-American economist Alex Tabarrok said.
…“There is this old story that pollution is bad, but it increases GDP… When the United States and Japan were developing, they were polluted. So India and China also have to go through that stage of pollution — so that they get rich, and then they can afford to reduce pollution,” Tabarrok said.
“I want to say that that story is wrong. What I want to argue is that a lot of the new research indicates that we may be in a situation where we could be both healthier and wealthier at the same time by reducing pollution,” he said.
…At the seminar, Tabarrok pointed out that expecting people to make sacrifices for the sake of future generations is not a politically fruitful way to deal with pollution.
Citing the issue of crop burning in India, he said farmers are not going to be inclined to change their behaviour if they are told to stop stubble burning for the sake of Delhi residents.
“However, if these farmers are made aware of how the crop burning harms them and their families and affects their soil quality, they are more likely to participate in mitigation measures,” he said.
I was pretty tough on government policy as Business Today India reported:
More than half of India’s population lives in highly polluted areas. Research by Greenstone et al (2015) proves that 660 million people live in areas that exceed the Indian Ambient Air Quality Standard (NAAQS) for fine particulate pollution. In this context, having measures such as banning e-cigarettes and having odd-even days for vehicles to solve the problem of air pollution seems ridiculous, says Alex Tabarrok, Professor of Economics at the George Mason University and Research Fellow with the Mercatus Centre. “These are not appropriate solutions to the scale and the dimensions of the problem,” he says.
In recent years, new research has significantly increased my belief that air pollution has substantial negative effects on productivity, IQ and health (see previous posts). Research in the field is exploding which means that there must also be more false positives. Consider two recent papers. The first, The Real Effect of Smoking Bans: Evidence from Corporate Innovation by Gao et al. finds that smoking prohibition increased patenting!
We identify a positive causal effect of healthy working environments on corporate innovation, using the staggered passage of U.S. state-level laws that ban smoking in workplaces. We find a significant increase in patents and patent citations for firms headquartered in states that have adopted such laws relative to firms headquartered in states without such laws. The increase is more pronounced for firms in states with stronger enforcement of such laws and in states with weaker preexisting tobacco controls. We present suggestive evidence that smoke-free laws affect innovation by improving inventor health and productivity and by attracting more productive inventors.
But the second, Do Firms Get High? The Impact of Marijuana Legalization on Firm Performance, Corporate Innovation, and Entrepreneurial Activity by Wang et al. finds that marijuana legalization increased patenting!
We find that state-level marijuana legalization has a positive financial impact on firms, likely by affecting firms’ human capital. Firms headquartered in marijuana-legalizing states receive higher market valuations, earn higher abnormal stock returns, improve employee productivity, and increase innovation. Exploiting firm level inventor data, we directly test the human capital channel and find that post legalization, firms retain inventors that become more productive and recruit more innovative talents from out of state. We also find that marijuana-legalizing states experience an increase in the number of new startups and venture capital investments.
Would anyone have been surprised if these two papers had shown exactly the opposite results? Indeed, there is some evidence that nicotine is solid cognitive enhancer and Tyler recently argued, on the basis of good evidence, that pot makes people dumb. Is it a coincidence that anti-cigarette and pro-pot papers appear as the country moves in this direction? Social desirability bias also applies to research. So no knock on either paper but I am unconvinced. As I like to say, trust literatures not papers.
Hat tip: The excellent Kevin Lewis.
The Lancet Commission on Pollution and Health, an authoritative review with well-over a dozen distinguished co-authors, is unusually forthright on the effect of pollution, most especially lead, on IQ. I think some of their numbers, especially in paragraph three, are too large but the direction is certainly correct.
Neurotoxic pollutants can reduce productivity by impairing children’s cognitive development. It is well documented that exposures to lead and other metals (eg, mercury and arsenic) reduce cognitive function, as measured by loss of IQ.168
Loss of cognitive function directly affects success at school and labour force participation and indirectly affects lifetime earnings. In the USA, millions of children were exposed to excessive concentrations of lead as the result of the widespread use of leaded gasoline from the 1920s until about 1980. At peak use in the 1970s, annual consumption of tetraethyl lead in gasoline was nearly 100 000 tonnes.
It has been estimated that the resulting epidemic of subclinical lead poisoning could have reduced the number of children with truly superior intelligence (IQ scores higher than 130 points) by more than 50% and, concurrently, caused a more than 50% increase in the number of children with IQ scores less than 70 (figure 14).265 Children with reduced cognitive function due to lead did poorly in school, required special education and other remedial programmes, and could not contribute fully to society when they became adults.
Grosse and colleagues 46 found that each IQ point lost to neurotoxic pollution results in a decrease in mean lifetime earnings of 1·76%. Salkever and colleagues 266 who extended this analysis to include the effects of IQ on schooling, found that a decrease in IQ of one percentage point lowers mean lifetime earnings by 2·38%. Studies from the 2000s using data from the USA 267,268 support earlier findings but suggest a detrimental effect on earnings of 1·1% per IQ point.269 The link between lead exposure and reduced IQ 46, 168 suggests that, in the USA, a 1 μg/dL increase in blood lead concentration decreases mean lifetime earnings by about 0·5%. A 2015 study in Chile 270 that followed up children who were exposed to lead at contaminated sites suggests much greater effects. A 2016 analysis by Muennig 271 argues that the economic losses that result from early-life exposure to lead include not only the costs resulting from cognitive impairment but also costs that result from the subsequent increased use of the social welfare services by these lead-exposed children, and their increased likelihood of incarceration.
Dean Spears, one of the authors of Where India Goes has a new book on air pollution in India, Air. When I reviewed Where India Goes in 2017 I said it was the best social science book I had read in years. Spears is able to accurately explain academic work–much of it his own and with co-authors–in accessible language and to combine that with on-the-ground reporting to produce a book that is both informative and full of human interest. He brings the same skills to Air.
As Spears shows, pollution is killing Indians, especially babies, and those it doesn’t kill it harms as seen in statistics on stunting and respiratory disease. Spears isn’t naive, however, he knows that manufacturing is also bringing tremendous benefits. The issue, however, is that a lot of pollution in India comes from relatively low value activities like burning crops. Moreover, solar power in India is cost competitive with coal today, even before taking into account health benefits. Thus, the harms of pollution are tragic because they are unnecessary.
If the costs of pollution exceed the benefits why isn’t something being done? One of the things I like about Air is that it is clear that pollution in India is both a market failure and a government failure. The government has been slow to respond to pollution because much of the public remains unaware of pollution’s true cost and much of the true cost is born by children and future people who have no vote. In the meantime, the government enhances rational ignorance by refusing to fund even the most basic equipment to measure where and when pollution ebbs and flows. Instead the government engages in virtue-politics by banning plastic bags and creating odd-even restrictions on driving in Delhi. These activities are pointless, even counter-productive, but they are well publicized and the appearance of doing something matters more than reality.
Here’s one brilliant bit:
Just next to the Raebareli coal plant is a solar power plant. The solar plant is, in principle, capable of generating 10 MW. That capacity is 1 per cent of the 1000 MW capacity of the immediately neighbouring coal plant (which had another few hundred megawatts under construction when I talked with Gaurav).
I visited the solar plant on Independence Day. The ground around the solar panels was ﬂooded with August rain. A shoe destroying walk through the mud and water brought me to the control room in a small building. There, a cheerful young engineer from Bengaluru watched a bank of computer screens. A TV monitor reviewed a list of fifteen highlights of the Prime Minister’s holiday speech that morning. The control room was set up in a museum-like display. The apparent goal was to impress visitors with modern renewable energy and with colourful displays of General Electric–branded software. The young engineer was excited to show me the screens. He clearly wanted the message to be good.
It was not good. That cloudy day, most of the dots were red, not green. The screens reported that the solar plant was generating 60 kW. The engineer assured me that one day it had gotten up to 7500 kW. A megawatt is 1000 kilowatts. So, at 0.06 MW, the solar plant was producing less than 1 per cent of the 10 MW that the signboard at the entrance promised, which would have been 1 per cent of the coal plant.
It is not surprising that a solar plant does not generate much electricity if it is built beneath the smoke of a coal plant with 100 times the capacity. Ordinarily, one places solar plants in the path of direct sunlight. This one was placed in the path of visitors.
Addendum: Case in point. India today bans e-cigarettes because of health risks!
That is one of the news stories of the end of this week, namely that the Trump administration eliminated a previous Obama administration ruling on this, see Brad Plumer for details. That sounds horrible, doesn’t it?
I took a look at the cost-benefit study (pointed out on Twitter by Claudia Sahm, or try this link, and please note it was prepared by consultants, not by the government itself). I spent some time with these hundreds of pages, and they are not always easy to parse (my apologies to the authors for any misunderstandings). Anyway, I quickly came upon this and related passages (p.45, passim):
In summary, the Final Rule is expected to reduce employment by 124 jobs on average each year due to decreased coal mined while an additional 280 jobs will be created from increased compliance activity on average each year.
Of course those “newly created jobs” are a cost, not a benefit, and should be switched to the other side of the ledger. That is not what this study did. And if I understand p.4-31 correctly, this study is using a multiplier of about 2. This approach is completely wrong, and if it were right Appalachia would love a lot of this coal regulation for its job-creating proclivities, but of course the region doesn’t.
The claimed annual benefit from the changes, from the side of coal demand (not the only effects), is $78 million, fairly small potatoes. Note the study doesn’t consider what are commonly the most significant costs of regulation, namely distracting the attention of managers and turning companies into legal and regulatory cultures rather than entrepreneurial cultures. The study does mention uncertainty costs from regulation, although I could not find any quantification of them.
Furthermore, I am not able to scrutinize the introductory section “SUMMARY OF BENEFITS AND COSTS OF THE STREAM PROTECTION RULE” and figure out the final assessment of net benefits for the rule and where that assessment might come from. I find that worrisome, and paging through the study did not put my mind at ease in this regard.
Now, I know how this works. Many of you probably are thinking that we need to do whatever is possible to attack or shrink the coal industry, because of climate change. Maybe so! Maybe we want to stultify the coal companies, for reason of a greater global benefit. But a) there is still a role for evaluating individual policy changes by partial equilibrium methods and reporting on those results accurately, and b) “putting down the coal companies,” as you might a budgie, is not what the law says is the proper goal of policy.
Imagine holding an attitude that places the Trump administration as the actual defenders of the rule of law! Besides, don’t get too worked up (p.174):
Our analysis indicates that there will be no increase in stranded reserves under any of the Alternatives.
There is, however, a very small decline in annual coal production (pp.5-20, 5-21) from the rule that had been chosen. Water quality is improved in 262 miles of streams (7-26), in case you are wondering, that’s something but hardly a major impact and that almost entirely in underpopulated parts of the country. All the media coverage I’ve seen implies or openly states a badly exaggerated sense of total water impact, relative to this actual estimate (are you surprised?). Returning to the study, there is also no region-specific estimate of how large (or small) those water benefits might be, at least not that I could find (again, maybe I missed it, but I did find some language suggesting that no such estimate would be provided).
Chapter seven calculates the benefits of the resulting carbon emissions, but after reading that section my best estimate for those marginal benefits is zero, not the postulated $110 million. The “social cost of carbon” is actually an average magnitude, and it does not measure benefits from very small changes. Again, you might think there is an imperative to consider “this policy is conjunction with numerous other anti-coal changes,” but that is not what the law stipulates as I understand it and furthermore it hardly seems that many other anti-coal regulatory changes are on the way.
If it were up to me, I would not have overturned the coal/stream regulations, and my personal inclination is indeed to fight a war on coal. But if you look at the grounds for evaluation specified by law, and examine the cost-benefit study with even a slightly critical mindset, we don’t know what is the right answer on this individual policy decision. The study outlines nine different regulatory alternatives and it is not able to conclude which is best, nor is the quantitative thrust of the study aimed toward that end.
Mood affiliation aside, to strike this regulation down, as the Trump administration has done, is in fact not an indefensible action.
On a more practical political level, Trump wishes to send a signal to Appalachian voters that he is looking out for coal and looking out for them. This is actually a very weak action, and it was chosen because for procedural reasons it was quite easy to do. The more you complain about it, the stronger it looks, and that’s probably a more important fact than any of the particular details of this study. Whether you like it or not, the coal debate is not really one that favors the Democrats.
Addendum: Here is the CRS paper, which seems to be derivative of other work, most of all this study.